Boris Curk

University of Maribor

Papers

12

Total Citations

172

H-Index

6

About

Boris Curk is a robotics and control systems researcher whose work has significantly advanced the field of intelligent robot motion control, particularly through the integration of sliding mode control (SMC) with modern computational techniques. His research spans variable structure control (VSC), neural network-based control, perturbation estimation, and impedance control, with a consistent focus on making robotic systems robust against uncertainties and external disturbances. Curk's most influential contribution, "Neural Network Sliding Mode Robot Control" (1997, 58 citations), elegantly bridges machine learning and classical control theory by formulating neural network control as a class of variable structure systems, embedding robustness directly into the learning process. His closely cited work on observer-based sliding mode control (1994, 56 citations) introduced joint acceleration estimation and load compensation strategies that rendered control systems insensitive to parameter variations — a landmark result for nonlinear robotic systems. Beyond manipulator control, Curk extended his expertise to nonholonomic and underactuated systems, notably modeling and controlling the gyroscopic Powerball® device, demonstrating breadth across challenging mechanical configurations. With over 168 combined citations, his body of work remains a meaningful reference for researchers designing reliable, disturbance-tolerant controllers for advanced robotic applications.

Research Focus

Key Achievements

6
H-Index
12
Papers
172
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Neural network sliding mode robot control
58 citations · 1997
📈 Most Prolific Year: 1997 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: University of Maribor

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago